Haptic Intelligence with Katherine J. Kuchenbecker - #491
Today we’re joined Katherine J. Kuchenbecker, director at the Max Planck Institute for Intelligent Systems and of the haptic intelligence department. In our conversation, we explore Katherine’s research interests, which lie at the intersection of haptics (physical interaction with the world) and machine learning, introducing us to the concept of “haptic intelligence.” We discuss how ML, mainly computer vision, has been integrated to work together with robots, and some of the devices that Katherine’s lab is developing to take advantage of this research. We also talk about hugging robots, augmented reality in robotic surgery, and the degree to which she studies human-robot interaction. Finally, Katherine shares with us her passion for mentoring and the importance of diversity and inclusion in robotics and machine learning. The complete show notes for this episode can be found at twimlai.com/go/491.
10 Kesä 202138min
Data Science on AWS with Chris Fregly and Antje Barth - #490
Today we continue our coverage of the AWS ML Summit joined by Chris Fregly, a principal developer advocate at AWS, and Antje Barth, a senior developer advocate at AWS. In our conversation with Chris and Antje, we explore their roles as community builders prior to, and since, joining AWS, as well as their recently released book Data Science on AWS. In the book, Chris and Antje demonstrate how to reduce cost and improve performance while successfully building and deploying data science projects. We also discuss the release of their new Practical Data Science Specialization on Coursera, managing the complexity that comes with building real-world projects, and some of their favorite sessions from the recent ML Summit.
7 Kesä 202140min
Accelerating Distributed AI Applications at Qualcomm with Ziad Asghar - #489
Today we’re joined by Ziad Asghar, vice president of product management for snapdragon technologies & roadmap at Qualcomm Technologies. We begin our conversation with Ziad exploring the symbiosis between 5G and AI and what is enabling developers to take full advantage of AI on mobile devices. We also discuss the balance of product evolution and incorporating research concepts, and the evolution of their hardware infrastructure Cloud AI 100, their role in the deployment of Ingenuity, the robotic helicopter that operated on Mars just last year. Finally, we talk about specialization in building IoT applications like autonomous vehicles and smart cities, the degree to which federated learning is being deployed across the industry, and the importance of privacy and security of personal data. The complete show notes can be found at https://twimlai.com/go/489.
3 Kesä 202139min
Buy AND Build for Production Machine Learning with Nir Bar-Lev - #488
Today we’re joined by Nir Bar-Lev, co-founder and CEO of ClearML. In our conversation with Nir, we explore how his view of the wide vs deep machine learning platforms paradox has changed and evolved over time, how companies should think about building vs buying and integration, and his thoughts on why experiment management has become an automatic buy, be it open source or otherwise. We also discuss the disadvantages of using a cloud vendor as opposed to a software-based approach, the balance between mlops and data science when addressing issues of overfitting, and how ClearML is applying techniques like federated machine learning and transfer learning to their solutions. The complete show notes for this episode can be found at https://twimlai.com/go/488.
31 Touko 202143min
Applied AI Research at AWS with Alex Smola - #487
Today we’re joined by Alex Smola, Vice President and Distinguished Scientist at AWS AI. We had the pleasure to catch up with Alex prior to the upcoming AWS Machine Learning Summit, and we covered a TON of ground in the conversation. We start by focusing on his research in the domain of deep learning on graphs, including a few examples showcasing its function, and an interesting discussion around the relationship between large language models and graphs. Next up, we discuss their focus on AutoML research and how it's the key to lowering the barrier of entry for machine learning research. Alex also shares a bit about his work on causality and causal modeling, introducing us to the concept of Granger causality. Finally, we talk about the aforementioned ML Summit, its exponential growth since its inception a few years ago, and what speakers he's most excited about hearing from. The complete show notes for this episode can be found at https://twimlai.com/go/487.
27 Touko 202155min
Causal Models in Practice at Lyft with Sean Taylor - #486
Today we’re joined by Sean Taylor, Staff Data Scientist at Lyft Rideshare Labs. We cover a lot of ground with Sean, starting with his recent decision to step away from his previous role as the lab director to take a more hands-on role, and what inspired that change. We also discuss his research at Rideshare Labs, where they take a more “moonshot” approach to solving the typical problems like forecasting and planning, marketplace experimentation, and decision making, and how his statistical approach manifests itself in his work. Finally, we spend quite a bit of time exploring the role of causality in the work at rideshare labs, including how systems like the aforementioned forecasting system are designed around causal models, if driving model development is more effective using business metrics, challenges associated with hierarchical modeling, and much much more. The complete show notes for this episode can be found at twimlai.com/go/486.
24 Touko 202140min
Using AI to Map the Human Immune System w/ Jabran Zahid - #485
Today we’re joined by Jabran Zahid, a Senior Researcher at Microsoft Research. In our conversation with Jabran, we explore their recent endeavor into the complete mapping of which T-cells bind to which antigens through the Antigen Map Project. We discuss how Jabran’s background in astrophysics and cosmology has translated to his current work in immunology and biology, the origins of the antigen map, the biological and how the focus was changed by the emergence of the coronavirus pandemic. We talk through the biological advancements, and the challenges of using machine learning in this setting, some of the more advanced ML techniques that they’ve tried that have not panned out (as of yet), the path forward for the antigen map to make a broader impact, and much more. The complete show notes for this episode can be found at twimlai.com/go/485.
20 Touko 202141min
Learning Long-Time Dependencies with RNNs w/ Konstantin Rusch - #484
Today we conclude our 2021 ICLR coverage joined by Konstantin Rusch, a PhD Student at ETH Zurich. In our conversation with Konstantin, we explore his recent papers, titled coRNN and uniCORNN respectively, which focus on a novel architecture of recurrent neural networks for learning long-time dependencies. We explore the inspiration he drew from neuroscience when tackling this problem, how the performance results compared to networks like LSTMs and others that have been proven to work on this problem and Konstantin’s future research goals. The complete show notes for this episode can be found at twimlai.com/go/484.
17 Touko 202137min
